Statistics II

After successful completion of this course the student:- can compute and interpret statistical tests and confidence intervals,- can compute and report power and effect sizes- can fit and analyze results from the ANOVA model (one- and two-way),- can fit and analyze results from the regression model (simple and multiple),- can interpret interaction effects (categorical x categorical in ANOVA/regression, continuous x continuous in regression),- can create and use code variables,- can fit and analyze results from the logistic regression model,- is able to read research papers using some of these methodologies discussed in the course.

Omschrijving

The central theme of this course is the deep understanding of statistical inferential models such as ANOVA and regression. After having learned how to describe, process, and perform basic inference on empirical data (courses Statistics Ia and Statistics Ib), students will now be introduced to some of most widely used statistical models in the social sciences. The knowledge to be acquired in this course is fundamental to enable students to properly analyze data and to make sound inferences. This will have a direct impact on the students' success on other courses in the curriculum such as Research Methods and the bachelor thesis, in which data will most likely need to be analyzed.The topics covered by this course include analysis of variance, simple and multiple regression analysis, logistic regression, and nonparametric tests. In all cases the goal is to show how each technique can be applied, under which conditions the analyses hold, and how the results can be interpreted and reported.The basic principles of these techniques will be discussed and explained in the lectures. During the practical classes, exercises will be made (using software: SPSS, JASP and/or R, and manually) in order to gain insight in how to apply the methods in practical situations. Practical classes are built with two goals in mind: Think about the theoretical framework of the analysis being conducted, and learn how to conduct it in practice. Computer assignments requiring students to apply some of the statistical techniques learned in the course to data will also be provided in the practical classes.